1. Field of the Invention
The present invention generally relates to radiocommunications network planning. More particularly, the present invention relates to radiocommunications planning of a network for mobile terminals, including a number of (large or small) cells distributed over a particular geographic area or territory.
2. Overview of the Related Art
A radiocommunication network system making use of the concept of cellular network enables significant increase of overall system capacity, but requires planning and dimensioning process for radiocommunication network apparatus operating in the radiocommunication network system. A first phase of such planning and dimensioning process is computing the so-called coverage area, i.e., extent and features of an operative region around a radio base station wherein radioelectric signals (i.e., electromagnetic signals propagating as waves over the air) radiated out from the radio base station and received by a mobile terminal (typically, a user terminal) are still able to ensure predefined requirements for a satisfactory quality of service. Usually, such predefined requirements comprise radioelectric strength (or other parameters related thereto) of the radioelectric signal received by the user terminal and radiating out from the radio base station.
A traditional coverage area computation, sometimes also referred to as coverage area prediction, is carried out by a proper algorithm using a low environment resolution data, i.e., by taking into account data describing the features of the environment within elementary areas, generally known as pixels, having a side of 50 or 100 meters. An example of coverage area algorithm is called RASPUTIN (Radio Strength Prediction Using Territorial Inputs), which is a propagation model tool that takes into account different aspects of radioelectric propagation phenomena for predicting coverage area of a single radio base station; more particularly, such aspects typically may include both radioelectric signal strength radiated therefrom (i.e., power radiating out from the radio base station) and databases information about territory (morphological, urbanization and orographic factors), which are combined to each other in order to predict the radioelectric signal propagation from the radio base station, and thus loss phenomena from which to evaluate coverage area of the radio base station.
Specifically, the propagation model implemented in RASPUTIN algorithm splits the radioelectric propagation phenomena into two main components: smooth earth effects and shadowing effects of the orographic obstacles. The smooth earth effects of the radioelectric propagation phenomena are taken into account by considering basic propagation curves, according to semi-empirical relationships which consider radioelectric signal power and frequency, effective height of the radio base station (i.e., of transmitting element or antenna thereof) with respect to the user terminal, distance from the radio base station and the user terminal, and without considering other parameters. In other words, the basic propagation curves are indicative of the radioelectric signal strength attenuation, also known as radioelectric signal propagation loss, in an open area, i.e., an area empty of trees, buildings or architectural structures made by human beings.
To the radioelectric signal strength attenuation or radioelectric signal propagation loss is then applied a correction factor given by building density and vegetation or greenery effects. More particularly, in RASPUTIN the effects due to local urbanization around the user terminal relate to the building density parameter, which is a surface parameter defined as percentage of area covered by buildings, with reference to a given standard grid size (for example, 230×230 m). Such a parameter usually ranges from very low values (<5%) for open (rural) zones, to values above about 60-70% for very densely built-up areas (historical town centers). This approach provides a quantitative identification of the type of the area under examination. Furthermore, RASPUTIN propagation model evaluates also the effects of greenery on the radioelectric signal propagation starting from knowledge of the vegetated areas distribution.
The shadowing effects due to orographic obstacles are instead taken into account by considering more complex propagation models, which require an interaction with territorial data bases. Starting from a radio base station, RASPUTIN algorithm scans the surrounding area along radial directions with a suitable angular step (typically, 0.5 degrees). For each direction, a data base interface provides the radial terrain height profile along which the field strength computation should be performed.
RASPUTIN algorithm considers the diffraction effects by using a prediction model based on the Huyghens-Fresnel diffraction theory. Accordingly, a single obstacle is assumed to be a perfectly absorbing half-plain screen (“knife-edge” approach), whose diffraction effects can be easily calculated, as long as the signal wavelength is negligible with respect to obstacle size and distances from both transmitting and receiving sites. The approximation consists of supposing the obstacle having no thickness along the propagation direction and being infinitely extended in the orthogonal section, respectively, and neglecting its real electromagnetic properties. In other words, starting from orographic parameters, an altimetric profile is determined all along each scanning line, and the interaction effects with the possible natural obstacles arranged along the scanning lines (involving radioelectric signal strength attenuation) are computed by resorting to the classic Huyghens-Fresnel theory, according to which such interaction effects may be assessed with adequate reliability by replacing each natural obstacle with an equivalent virtual obstacle (screen) having a knife edge shape, a height equal to the natural obstacle, an infinitesimal thickness, endlessly extending perpendicularly to the propagation direction, and perfectly absorbing the incident electromagnetic signal.
In the state of the art, other solutions are known for predicting areas coverage.
For example, in Stankovic, Z.; Milovanovic, B.; Veljkovic, M.; Dordevic, A “The hybrid-neural empirical model for the electromagnetic field level prediction in urban environments”, 2004 Seventh Seminar on Neural Network Applications in Electrical Engineering (IEEE Cat. No. 04EX871), is presented an application of multilayer perceptron networks for calculating electromagnetic wave path loss in an urban environment for propagation through an area with low or high buildings. A hybrid neural-empirical model, created in two phases, is proposed. The first phase implies the realization of an approximate (coarse) propagation model based on measured values. This model determines the propagation loss from the beginning of the area, based on the distance from the area beginning, the average building density, the partial loss of a single building, the distance from the transmitter and the exponential loss index of the area. In the second phase, a neural network and the approximate model are integrated in the hybrid (fine) model of the propagation area. The input parameters for the neural network are the distance from the area beginning and the average height of buildings in that area, while the output parameter is the partial loss of a single building. This value is used in the approximate model, in order to obtain the propagation area model with higher accuracy.
In Balis, P. G.; Hinton, O. R. Author Affiliation, Panafon S A, Athens, Greece, “UTD-based model for prediction of propagation path loss and shadowing variability in urban mobile environments”, IEE Proceedings—Microwaves, Antennas and Propagation, vol. 144 no. 5, pp. 367-71, a new uniform-theory-of-diffraction (UTD-) based approach for cellular-mobile-radio-propagation modeling is presented. Buildings are represented as conducting halfplanes or screens, and the model includes the effect of building-height variation along all intervening screens between base station and mobile. The proposed model has a low computational complexity and could be applicable to small urban cells over regular terrain, with buildings of nonuniform height. Results from the model seem to be in very close agreement with experimental observations (at 465 MHz, 927 MHz and 851 MHz), and seem to accurately predict observed trends in the dependence of path loss and its variability on frequency, range, building-height variation and screen spacing.
Moreover, in Ichitsubo, S., Kimura, M. “A propagation model for mobile radio propagation loss in an urban area at 800 MHz”, Electronics and Communications in Japan, Part 1 (Communications), vol. 76, no. 10, pp. 91-104, there is proposed a method to understand the propagation structure of the microcells with a tall and medium-height antenna in an urban area; by founding fundamental propagation parameters and constructing the structural model of the propagation loss. The fundamental propagation parameters were obtained based on the multivariable analysis of the propagation data at 800 MHz measured in the Tokyo Metropolitan area. These parameters are the distance between the transmitter and receiver, the average building height between the transmitter and receiver, and the base-station height which have high correlation and regression coefficients with the propagation loss. The relationship of parameters obtained from the model is (20-alpha)log(h) for the base-station height characteristics and (alpha-20)log(H) for the building height characteristics if the distance characteristics are alphalog(d). The relationships of coefficients of the conventional estimation equation and the regression equation obtained by the measured data almost agreed with those of the model so that the validity of the model was confirmed.